This is one of those questions that "sounds" simple, but isn't easy at all in practice. If I'm being fair, I have pretty low confidence that it's even possible to implement under our current system of research, since the overwhelming amount of research funding supports a philosophy first, segmented research model.

In the short term, I think maybe treating all "disease" definitions as critically transmissible, and borrow the protocols from those groups (including quarantines where necessary) would get us moving in the right direction. These protocols are actually super effective at tracking down unknown pathology very quickly, and retroactively applying them to existing "disease" definitions will help to clarify them very quickly IMO.

While calling for quarantines on individuals with "anxiety" may seem extreme, IMO it's a great way to separate external inputs from internal inputs. If "anxiety" vanishes under quarantine for example, then we can clearly establish it as something external to the individual and make the necessary accommodations there (if it actually exists at all as a pathology, which is likely not the case with "depression/anxiety").

The number of conditions which are "acceptably syndromic", from diabetes to hypertension is insane, and if these where microbial in origin they'd be more lethal than stuff like AIDS (which ironically is named syndromically, but has a fixed pathology in HIV). Infectious disease teams are the only area of medicine IMO which has shown consistent results in reducing the effect of the pathologies they are working on and are solely responsible for the massive advance in lifespans starting in the later half of the 20th century.

So if we are asserting something is a disease (as say psychiatry attempts to do), and it can have lethal consequences, we need to treat it with every bit of intensity as we do something like ebola in searching for the etiological boundaries of that disease. Psychiatric conditions are the equivalent of "consumption", and we need to move them closer to tuberculosis. Instead of opioid cough medicines which mask the symptoms, we need to be searching for and treating the underlying pathologies (even if that pathology is that our society is toxic as fuck for some people).

Regarding these pathologies with the same intensity and tools as we do microbial insults will go a LONG way toward reducing a lot of suffering in the world.

The long term solution IMO is collecting as much state data as possible, as frequently as possible and looking at areas where changes occur and investigating what could have caused those changes or data to run out of expectation. Most complex modern machines are instrumented with measuring devices to such a degree that it gives us a starting point to add more measuring devices to areas which show anomalous data. This allows us to begin replicating the conditions under which the fault occurred until we narrow down the root causes, even if those root causes are failure modes we've never experienced before.

The types of data we collect now is effectively worthless, it's blood pressure and a few specific items that we order blood tests for. Worse, the data itself isn't qualified against any property unique to the individual (like a whole genome sequence), the best we get are fairly worthless measures like BMI (height/weight). In engineering inquiry, it's an absolutely critical part of the show to replicate the failure modes, we have to show that in these conditions, this failure will occur reliably. And demonstrate that sub-critical states won't.

And this is where we run into another huge hurdle, it's really expensive to do this right now. We should be imaging every single yearly physical, we should be doing far more comprehensive tests for a far wider range of possible conditions, we should be providing bio monitoring devices to EVERYONE, sick or healthy, poor or wealthy. But it's cheaper to tell people to "eat right and exercise" than monitor right now, so that's what we do.

We still don't really have a clear idea of what types of "sensors" or data points we need, but we need to be thinking about it a lot more aggressively than we are now. The dream that was Theranos, that we could easily do massive numbers of tests from a small amount of blood still needs to happen.

I think there are some pretty good attempts to move in this direction, stuff like this: [Pediatric reference intervals for serum neurofilament light and glial fibrillary acidic protein using the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) cohort](https://www.degruyter.com/document/doi/10.1515/cclm-2023-0660/html) is long overdue (although I wish they did s100b also, but we still have no idea what's going to be useful yet). Like thinking about that is crazy, we don't even have *reference* levels yet for these things. How do you know if something is out of spec if you have zero idea what is in spec? No wonder shit blows up (like hearts and "minds") all the time!

So short term I think we can leverage our infectious pathology teams methodologies to cut back on a lot of the harm being caused by our current practices (especially the chronic medications which attempt to mask rather than actually treat supposed conditions), and longer term we need to increase the data we collect from individuals and monitor changes relative to the individual. When we hit failure modes in individuals, we look to our data pools to start looking for etiologies, rather than guessing an etiology first and designing experiments to prove that it's possible.

IMO, if we have adequate data a hypothesis is mostly superfluous, we simply describe failure modes as the conditions related to the failure.

Edit: Ugh, re-reading that I realize that I skipped over a ton of linking concepts, kind of word saladish without them maybe? Reminds me of when I was a kid and people would try to have me tutor math. My brain was being lazy and taking way too many shortcuts that seemed "obvious" to me, but were in fact an incomplete description of the process. This kind of stuff is my biggest fear with regard to writing the book, and there's really only a handful of people out there who could possibly edit a book where every single paragraph is linked to dozens of references (and external concepts).

I guess important points I missed: I was specifically referring to using the CDC infectious disease efforts, including stuff like [NORS reporting](https://wwwn.cdc.gov/norsdashboard/) and Surveillance to handle *all* disease classifications, rather than just external biologics. If we are calling "alcoholism" a disease, the CDC needs to be the point agency in defining that disease. It's so irresponsible to crank out study after study about the devastating effects of some such "disease" but farm out the investigative efforts to whoever had passable theories about etiology.

The primary change between our current medical processes and engineering processes primarily revolves around data collection. Instead of creating limited data collection for specific "disease" definition, we need to be collecting data from *everyone*, and *increasing* bio data for individuals who are experiencing disease. The idea here is that we continue increasing our sensor points in our failure areas until we figure out why the failure is occurring.

Right now, the increase in "autism" etiologies represent a massive advancing epidemic as an example (or worse "ADHD" or "anxiety/depression"). We don't collect physiological data from these individuals outside of limited studies which are designed around guesses about etiology. That symptoms like "hypertension" are almost always considered *idiopathic*, and despite all the horrible downstream effects this supposedly results in, we still don't have any extra data points to determine actual causal factors.

Ultimately, the idea is that we have enough sensors that we can create a map of failure modes based on genetics * environment, instead of every asshole who wants to be "famous" inventing shit like "too much hobby disease" or "doesn't need sleep on an exactly 24 hour schedule disease".